Multi-dimensional beamforming device

ABSTRACT

A multi-dimensional beamforming device that performs consecutive one-dimensional operations. For example, beamsteering for a two-dimensional array can be include a projection of a beam onto each of the respective axes of the array. In such a device, a first beamforming processing element is used to form multiple beams for each array output along a given row. In a preferred embodiment, sequential output vectors from the first processing element are then applied to a transposing or corner turning memory and the data are reformatted such that all elements on a given column of the array are applied to a second beam forming processing element.

RELATED APPLICATIONS

This application is a continuation application of InternationalApplication No. PCT/US98/02291, filed on Feb. 3, 1998, which is acontinuation-in-part application of U.S. Ser. No. 08/965,663 filed onNov. 6, 1997, now U.S. Pat. No. 6,111,816, which claims the benefit ofU.S. Provisional Patent Application No. 60/036,837, filed on Feb. 3,1997, the entire teachings of the above applications being incorporatedherein by reference.

BACKGROUND OF THE INVENTION

One use of sensor arrays is to isolate signal components that aretraveling from, or propagating to, a particular direction. They find usein a number of different applications. For example, sonar systems makeuse of sensor arrays to process underwater acoustic signals to determinethe location of a noise source; arrays are also used in radar systems toproduce precisely shaped radar beams. Array processing techniques forisolating received signals are known as beamforming, and when the sameor analogous principles are applied to focus the transmission ofsignals, the techniques are referred to as beamsteering.

Considering the process of beamforming in particular, it is typicallynecessary to use a fairly large number of signal processing componentsto form the desired directional beams. The signal from each sensor istypically divided into representative components by subjecting eachsignal to multiple phase shift, or time delay, operations which cancelthe equivalent time delay associated with the respective relativeposition of the sensor in the array. To form the directional beam thetime shifted signals from each sensor are then added together. Theimparted time delays are chosen such that the signals arriving from adesired angular direction add coherently, whereas those signals arrivingfrom other directions do not add coherently, and so they tend to cancel.To control the resulting beamwidth and sidelobe suppression, it istypical for each time delayed signal to be multiplied or “amplitudeshaded” by a weighting factor which depends upon the relative positionof the sensor in the array.

Beamforming in one dimension can thus be realized through a relativelystraight-forward implementation using a linear array of sensors and abeamforming processor, or beamformer, that delays each sensor output bythe appropriate amount, weights each sensor output by multiplying by thedesired weighting factor, and then sums the outputs of the multiplyingoperation. One way to implement such a beamformer is to use a tappeddelay line connected to each array element so that the desired delay forany direction can be easily obtained by selecting the proper output tap.The beam steering operation then simply consists of specifying theappropriate tap connections and weights to be applied.

However, a beamforming processor becomes much more complex when a twodimensional sensor array is used. Not only does the number of time delayoperations increase as the square of the size of the array, but also thephysical structures required to connect each sensor to its correspondingdelay becomes complex. At the same time, each delay unit must beprovided with multiple taps for the formation of multiple beams. Theproblem can become prohibitively complicated when the simultaneousformation of multiple beams is required.

As to implementation choices, beamforming technology was originallydeveloped for detection of acoustic signals in sonar applications. Thebeamformers built for these early sonars used analog delay lines andanalog signal processing components to implement the sum and delayelements. Networks of resistors were then used to weight and sum theappropriately delayed signals. However, the number of beams that can beimplemented easily with such techniques is limited since each beamrequires many discrete delay lines, or delay lines with many taps andmany different weighting networks. As a result, it became common toshare a delay line by using scanning switches to sequentially look inall directions. However, with this approach only one beam is availableat a given time.

Recent advancements in integrated circuit electronics has provided thecapability to implement practical digital beamforming systems. In thesesystems a signal from each sensor is first subjected to analog todigital conversion prior to beamforming. The beamformers are implementedusing digital shift registers to implement the delay and digitalmultiplier components to implement the required weighting. The shiftregisters and multiplier components are typically controlled by commandsignals that are generated in general purpose computers using algorithmsor equations that compute the values of the delays and phase weightingsnecessary to achieve the desired array beam position. Beam control thusrequires fairly complex data processors and/or signal processors tocompute and supply proper commands; this is especially the case if morethan one beam is to be formed simultaneously.

For these reasons, few multi-dimensional multiple beam systems existthat can operate in real time with a minimum implementation complexity.

SUMMARY OF THE INVENTION

The invention is a beamsteering or beamforming device (generically, abeamforming device), that carries out multi-dimensional beamformingoperations as consecutive one-dimensional operations. In a preferredembodiment the two operations are interposed by a transpose operation.For example, beamforming for a two-dimensional array of sensors iscarried out as a set of projections of each desired output beam ontoeach of the two respective axes of the array.

Signal samples are periodically taken from each sensor in the array andthen operated on as a group, or matrix, of samples. A firstone-dimensional (1D) beamformer is used to form multiple beams for eachsensor output from a given row of the sample matrix. The multiple outputbeams from the first 1D beamformer are then applied to a transposingoperation which reformats the sample matrix such that samplesoriginating from a given column of the sensor array are applied as agroup to second one-dimensional (1D) beamformer.

The beamformer can be implemented in an architecture which eitheroperates on the samples of the sensor outputs in a series of row andcolumn operations, or by operating on the sample matrix in parallel. Inthe serial implementation, a group of multiplexers are used at the inputof the first 1D beamformer. Each multiplexer sequentially samples theoutputs of the sensors located in a given column of the array. Themultiplexers operate in time synchronization such that at any giventime, the outputs from the group of multiplexers provide samples fromthe sensors located in each row of the array.

The multiplexers then feed the first 1D beamformer that calculates theprojection of each row onto a first array axis, for each of the desiredangles. In the serial implementation, the first 1D beamformer isimplemented as a set of tapped delay lines formed from a series ofcharge coupled devices (CCDs). Each delay line receives a respective oneof the multiplexer outputs. A number of fixed weight multipliers areconnected to predetermined tap locations in each delay line, with thetap locations determined by the set of desired angles with respect tothe first array axis, and the weights depending upon the desired beamwidth and sidelobe supression. Each output of the first 1D beamformer isprovided by adding one of the multiplier outputs from each of the delaylines.

The serial implementation of the transposer uses a set of tapped delaylines with one delay line for each output of the first 1D beamformer.The tapped delay lines have a progressively larger number of delaystages. To provide the required transpose operation, samples are fedinto the delay lines in the same order in which they are received fromthe first 1D beamformer; however, the samples are read out of the delaylines in a different order. Specifically, at a given time, the output ofthe beamformer are all taken from a specific set of the last stages ofone of the delay lines.

Finally, the second 1D beamformer consists of a set of tapped delaylines, fixed weight multipliers and adders in the same manner as thefirst 1D beamformer. However, the weights and delays applied by thesecond 1D beamformer are determined by the set of desired angles to beformed with respect to a second axis of the array.

In a parallel implementation of the invention, the multiplexers are notused, and instead the outputs of the array are fed directly to a set ofparallel processing elements which operate on samples taken from all ofthe sensors simultaneously. Each processing element produces a set ofbeamformed outputs that correspond to the samples taken from one of therows of sensors beamformed at each of the desired angles with respect tothe first array axis. In this parallel implementation, the transposingoperation is carried out by simply routing the outputs of the processingelements in the first 1D beamformer to the appropriate inputs of thesecond 1D beamformer. The second 1D beamformer likewise is implementedas a set of parallel processing elements, with each processing elementoperating on beamformed samples corresponding to those taken from one ofthe columns of the array, beamformed at each of the desired angles withrespect to the second array axis.

In another preferred embodiment of the invention, a low power timedomain delay and sum beamforming processor involves programmable delaycircuits in sequence to provide a conformal acoustic lens. Thiselectronically adjustable acoustic conformed lens has a plurality ofsubarrays that can be separately controlled to adjust viewing angle andtheir outputs coherently summed for imaging.

The invention provides a substantial advantage over prior artbeamformers. For example, a device capable of steering up to one hundredbeams for a ten by ten sonar array can be implemented on a singleintegrated circuit chip operating at a relatively low clock rate of 3.5MegaHertz (MHZ), representing a continuous equivalent throughput rate ofapproximately 14 billion multiply-accumulate operations per second.

BRIEF DESCRIPTION OF THE DRAWINGS

This invention is pointed out with particularity in the appended claims.The above and further advantages of the invention may be betterunderstood by referring to the following description in conjunction withthe accompanying drawings, in which:

FIG. 1 is a block diagram of a serial implementation of a multiplesimultaneous beamformer fay according to the invention;

FIG. 2 illustrates the notation used herein to refer to various elementsin the sensor array and their beam transformations;

FIG. 3 is a three dimensional view of the array illustrating a beamformed therefrom together with projections of the beam onto a pair oforthogonal array axes;

FIG. 4 is a more detailed block diagram of the invention showing a firstone-dimensional beamformer, a transposer, and a second one-dimensionalbeamformer together with various matricies of sensor samples formed bythese components;

FIG. 5 is a block diagram of a serial implementation of aone-dimensional beamformer;

FIG. 6 is a block diagram of a serial implementation of the transposer;

FIG. 7 is a block diagram similar to that of FIG. 1, but showing aparallel implementation of the multiple simultaneous beamforming system;

FIG. 8 is a more detailed block diagram showing the interconnection ofcomponents for the parallel implementation;

FIG. 9 is a detailed block diagram of a processing element used in theparallel implementation;

FIG. 10 is a block diagram of a beamsteering system making use of theinvention; and

FIG. 11 is a block diagram of a higher dimensional implementation of themultiple simultaneous beamforming system.

FIG. 12 illustrates a beamforming process utilizing programmable delays,shading and weighting.

FIG. 13 illustrates an array of subarrays for an electronicallyadjustable acoustic conformal lens in accordance with the invention.

FIG. 14A illustrates an electronically controlled beamforming system inaccordance with the invention.

FIGS. 14B and 14C illustrate additional preferred embodiments of abeamforming system in accordance with the invention.

FIG. 15 illustrates a method of adjusting delays and shading in a scanpattern in accordance with the invention.

FIG. 16 illustrates a method for computing delay requirements inparallel to afford real time processing in accordance with theinvention.

FIGS. 17A-17E are schematic diagrams of systems in accordance with theinvention.

FIGS. 18A-18B illustrate transmit beamforming systems in accordance withthe invention.

FIG. 19 is a schematic illustration of an integrated circuit controllerelement in accordance with the invention.

FIG. 20 is another preferred embodiment of a channel controller.

FIG. 21A-21D illustrate sequential and parallel beamforming andassociated image plane scan patterns.

FIGS. 22A-22C illustrate image plane scan patterns for single processor,two processor and four processor systems.

FIG. 23 is an example illustrating sequential and parallel beamformingin a transducer array having 192 elements.

FIG. 24 illustrates a method of forming a Doppler sonogram in accordancewith the invention.

FIG. 25 illustrates a method of forming a color flow map over time usinga two dimensional array.

FIG. 26 illustrates a block diagram for a pulsed Doppler ultrasoundimaging system.

FIG. 27 illustrates a two-PDP system for color flow mapping.

FIG. 28. is a process flow diagram for color flow map analysis based ona fourier transform process.

FIG. 29. is a process flow diagram for a color-flow map based on anoptimal mean velocity.

FIG. 30 is a process flow diagram for a color-flow map based on across-correlation procedure.

The foregoing and other objects, features and advantages of theinvention will be apparent from the following more particulardescription of preferred embodiments of the invention, as illustrated inthe accompanying drawings in which like reference characters refer tothe same parts throughout the different views. The drawings are notnecessarily to scale, emphasis instead being placed upon illustratingthe principles of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Turning attention now to the drawings, FIG. 1 illustrates a system 10for use with a two-dimensional, planar sensor array according to theserial implementation of the invention. The system 10 shown in FIG. 1 isa beamforming system, that is, system 10 operates with sensors 12 thatdetect received signals. However, as will be understood from thefollowing description, the invention also applies to beamsteeringsystems where the sensors 12 are transmitting signals, and the signaldirections are reversed.

The beamforming system 10 consists of a number of sensors 12 arranged ina planar array 14, a number, n, of multiplexers 17-0, 17-1 . . .17-(n−1), a first one-dimensional (1D) beamformer 18, a transposer 20,and a second 1D beamformer 22.

The array 14 consists of a number of sensors 12 arranged in an array ofm rows 15-0, 15-1, 15-(m−1), each row having n sensors 12, and n columns16-0, 16-1, 16-(n−1) having m sensors 12. The array may or may not besquare, that is, n may or may not be equal to m.

The exact type of sensor 12 depends upon the particular use of thesystem 10. For example, in a system 10 intended for application tosonar, each sensor 12 is a hydrophone. In an application to radarsystems, each sensor 12 is an antenna.

The remainder of the components of the system 10 operate to formmultiple output beams 24 simultaneously. Before proceeding with adetailed description of the structure and operation of the system 10, itis helpful to define a notation to refer to the various sensors 12 andas shown in FIG. 2. In particular, each of the (n×m) sensors 12 in thearray 14 are referred to herein with respect to its relative horizontaland vertical position (x,y). Thus, for example, the notation Dx,yrepresents the signal provided by the sensor 12 located at column numberx, row number y.

The notation Dx,v is used to refer to a beam formed using all of thesensors located in a given column, x, at an particular angle, v, withrespect to the array 14. Dw,y indicates a beam formed at a particularangle, w, using the sensors 12 in a given row y at an angle w withrespect to the array. The notation Dw,v denotes the beam formed at a twodimensional angle (w,v) with respect to the array 14. Dw,v[t] indicatesa beam formed at angles (w,v) at a time, t, or a depth, t, from the(x,y) plane of the array 14.

With reference now to FIG. 3, the operation of the invention may bebetter understood. In particular, FIG. 3 illustrates the planar array 14in a three-dimensional view and an exemplary beam 26 formed on an angle(w,v) with respect to the (x,y) plane in which the array 14 is located.An additional third axis, z, is shown and is defined as being orthogonalto the (x,y) plane.

As can be seen from the illustration, the beam 26 formed at the angle(w,v) can be considered as having a pair of components projected upontwo planes formed by the z axis and each of the array axes x and y. Inparticular, the beam 26 has a first component 26-1 in the xz planeforming an angle w with respect to the x axis, as well as a secondcomponent 26-2 in the yz plane forming an angle v with respect to the yaxis.

This assumption that the beam 26 can be represented as a pair ofcomponents 26-1 and 26-2 projected onto the orthogonal planes xz and yzis based upon an assumption that a far field operation approximation isvalid for processing signals received from the array 14. The far fieldapproximation will be valid for an array 14 in most sonar applications,for example. In such applications, the sensors 12 may typically bespaced approximately one meter apart, with the sound source beinglocated at a distance of 100 meters or farther away from the array 14.Therefore, the far field approximation assumption is valid inapplications where the sensor spacing, 1, is much smaller than thedistance from the source being sensed. A difference of at least twoorders of magnitude between the array sensor spacing and the distance tothe source is sufficient for the approximation to be valid.

The operations required to form a number of desired beams 26 at a numberof angles (w,v) can thus be decomposed into a pair of successiveone-dimensional operation on the sensor outputs. Beam steering in agiven direction (w,v) is accomplished as the projection of the beam 26onto the xz plane forming an angle w with the x axis, followed by aprojection onto the yz plane forming an angle v with respect to the yaxis.

Returning now to FIG. 1, it can be seen that the first one-dimensional(1D) beamformer 18 thus performs the projection of the beam onto the xzplane, and that the projection onto the yz plane is performed by thesubsequent operations of the second 1D beamformer 22. The first 1Dbeamformer 18 forms a set of beams for each desired beam angle v bytaking samples of the signals output from the sensors 12 located in agiven 15 row of the array 14. The outputs from the first one-dimensionalbeamformer 18 are reordered by the transposer 20, to arrange thebeamformed outputs derived from a given column 16 together. This permitsthe second 1D beamformer 22 to perform the required operations at eachof the angles w, while at the same time permitting the second 1Dbeamformer 22 to have the same internal structure as the first 1Dbeamformer 18.

FIG. 4 is a more detailed view of the operation of the first 1Dbeamformer 18, the transposer 20, and second 1D beamformer 22. It isassumed that the number of beams to be formed is equal to the number ofsensors 12, such that a two dimensional array of beams 26 at each angle

(wi, vj) for I=o to n−1

and for j=0 to m−1

is to be formed. However, it should be understood that the beams neednot be the same dimension as the array, and indeed, the total number ofbeams 26 need not be the same as the total number of sensors 12.

The FIG. 4 shows the inputs from the from the sensors 12 arranged assample matrices. In particular, the samples input to the first 1Dbeamformer 18,

(Di,j) for I=o to n−1

and for j=0 to m−1

are signal samples taken from the sensors located at each respectivecolumn and row position. The samples are operated on in two-dimensionalgroups, or matrices, by the system 10; the set of samples taken from thearray 14 is referred to as the matrix 30.

The first 1D beamformer 18 performs a beam forming operation along the xdirection at each of the desired beam angles w0, w1, . . ., w(n−1). Forexample, the output Dw0,y0 represents the result of beamforming at abeam angle w0 the samples having a row coordinate of zero. That is, theoutput Dw0, y0, indicates the result of the beamforming operation onsamples D0,0; D0,1; . . . , D0,(n−1) located in row 15-0 at one of thedesired beam angles w0. Likewise, Dw1,y0 corresponds to the output ofthe 1D beamformer 18 at beam angle w1, and so on.

The first beamformed matrix 32 output by the first 1D beamformer 18 thusrepresent input samples Dx,y beamformed along the x axis with each ofthe respective desired beam angles w0, w1, . . . , w(n−1).

The transposer 20 transposes the rows and columns of the firstbeamformed matrix 32 to produce a transposed matrix 34. The transposedmatrix 34 arranges the beamformed samples having the same correspondingy value located in a given column, and the beamformed samples having thesame beam angle, w, located in a given row. This permits the second 1Dbeamformer to perform the 1D beamform operation on the samples in eachrow, with different angles vj, for j=0 to (m−1).

As a result, the output matrix 36 from the second 1D beamformer 22represents the two-dimensional beamformed outputs 24, with the outputDw0,v0 representing the beam at angle (w0,v0), the output Dw0,v1corresponding to the beam at angle (w0,v1), and so on. In other words,the sample outputs from the second 1D beamformer 22 correspond to alltwo dimensional beams formed the desired angles

(wi,vj) for I=0 to n−1, and

for j=0 to m−1.

Although FIG. 4 illustrates 1D beamformer 18 that translating along thex axis before 1D beamformer 22 translates along the y axis, it should beunderstood that the order of the 1D beamforming operations can beinterchanged.

For the serial pipelined implementation of the invention, the matricesin FIG. 4 can also be interpreted as showing the time sequence in whichthe samples are operated upon by the first 1D beamformer 18, transposer20, and second 1D beamformer 22. For example, in FIG. 4, each column inthe matrix 30 represents samples taken from a particular one of the nmultiplexers 17 in FIG. 1. Therefore, the multiplexers 17 in FIG. 1sequentially select the output of one of the elements in a given column13. For example, the first multiplexer 17-0 sequentially samples theoutputs of the sensors 12 located in the first column 16-0 of the array14. Likewise, a second multiplexer 17-1 sequentially samples the outputof the sensors 12 located in a second column 16-1 of the array 14. Themultiplexers operate sequentially such that each sensor 12 iseffectively sampled at a sampling rate of fs.

The leftmost column of the matrix 30 indicates the order of the outputstaken from the first multiplexer 17-0 of FIG. 1. The time sequencebegins at the bottom row of the matrix 30 and works up the columns.Therefore, the samples are output by multiplexer 17-0 in a sequenceDx0,y0; Dx0,y1; . . . ; Dx0,ym−1. Since the multiplexers 17 operate inparallel and in row synchronization, the samples taken from the sensors12 located on the first row, 15-0, that is, samples Dx0,y0; Dx1,y0;Dx2,y0; . . . , Dx(n−1),y0 are applied at the same time to the first 1Dbeamformer 18. Next, the samples from the second row 15-1, or samplesDx0,y1; Dx1,y1; . . . , Dx(n−1),y1 are applied to the first 1Dbeamformer 18, and so on.

Since the first 1D beamformer 18 performs a 1D beamforming operation onthe samples in a given row 15, the first 1D beamformer can beimplemented as a pipelined device such that a new row of samples can beimmediately applied to the device and the operation repeated.

FIG. 5 is a more detailed view of the serial pipelined implementation ofthe first beamformer 18 for a 10 by 10 sensor array 14. The illustrated1D beamformer 18 consists of ten tapped delay lines 40-0, 40-1, . . .40-9, with a tapped delay line 40 being connected to the output from acorresponding one of the multiplexers 17-0, 17-1, . . . , 17-9. A firstgroup of multipliers 41-0-0, 41-0-1, . . . , 41-0-9 are associated withthe first tapped delay line 40-0, a second group of multipliers 41-1-0,41-1-1, . . . 41-1-9 are associated with the second tapped delay line40-1, and so on. The notation Dx0 above the first tapped delay line 40-0indicated that the “x0” samples, that is, samples Dx0,y0; Dx0,y1; . . .; Dx0,y9 are applied to the input of tapped delay line 40-0 in arepeating sequence.

The tapped delay lines 40 insert appropriate delays in the sensoroutputs to account for relative propagation delays of a signal from aparticular location. The delay lines 40 are each tapped such that theoutputs from a certain number of delay stages are provided to the inputof a multiplier 41.

The internal clock rate of each delay line 40 is ten times the inputsample rate, fs, to permit the sampling of ten sensors into each tappeddelay line 40. The total number of stages in each delay line 40 issufficient to provide the maximum delay associated with forming a beamat the maximum required one of the angles, w. In the illustratedimplementation, the total length of the delay line 40-0 shown isapproximately 1350 stages, with ten tap positions set to provide 10equally spaced apart angles, w. The position of the taps, that is theexact positions at which the inputs to the respective multipliers 41 istaken, depends upon the desired number of beams. The desired beam shapeis defined by the weights applied to the multipliers 41.

Thus for an array 14 forming ten beams from each row 15 of inputsamples, the first 1D beamformer 18 consists often tapped delay lines,each delay line having ten taps and ten multipliers 41.

If the number and position of the desired beams is known in advance, thetap positions and constant values input as weights to the multipliers 41can be hard wired or mask programmable.

The tapped delay lines 40 are preferably implemented as charge coupleddevice (CCD) type delay lines with fixed weight multipliers. A preferredimplementation of this invention uses a non-destructive sensing type ofcharge domain device described in a co-pending U.S. patent applicationSer. No. 08/580,427, filed Dec. 27, 1995 (MIT Case Number 7003), bySusanne A. Paul entitled “Charge Domain Generation and ReplicationDevices” the entire contents of which is hereby incorporated byreference.

The outputs of the multipliers 41 are then summed to accomplish thedesired multiple simultaneous beam forming functions. The weightedoutputs from the multipliers 40 are then simultaneously summed to formthe desired beam output along a given row. For example, the output Dw0is taken by summing the outputs of the last multipliers 41-0-9, 41-1-9,. . . , 41-9-9 associated with each of the tapped delay lines 40.

FIG. 6 shows a detailed block diagram of pipelined serial implementationof the transposer 20. In the implementation for a 10 by 10 array, thetransposer 20 contains ten parallel inputs which after ten consecutiveoutput sample time periods produces a transposed 10 by 10 transposedmatrix 34 according to FIG. 4. In this implementation for serialoperation each of the 10 inputs Dx0, Dx1, . . . Dx9 are fed to a simpletapped delay line 50-0, 50-1, 50-2 . . . 50-9. The tapped delay lines 50operate at the same clock rate, fs, as the input sampling rate.

The number of delay stages within each of the delay lines 50progressively increases as the column index. For example, the firsttapped delay line 50-0 has a length which is one more than the number ofrows, m, in the matrix, or 11 stages, the second delay line 50-1 is 12stages long and so on until the 10th delay line 50-9 is 20 stages long.Only the last 10 stages of each delay line 50 are tapped to provide foroutputs.

In operation, the taps associated with each delay line are enabled atthe same time in a time slot associated with that delay line. Forexample, at a first time p0 all of the taps from the first delay line50-0 are enabled in parallel to provide the ten output Dw0,y0; Dw0,y1; .. . , Dw0,y9. At a second time p1, only the tap from the second delayline 50-1 are enabled. The operation continues until a time p9 at whichthe taps on the last delay line 50-9 are enabled.

FIG. 7 is a block diagram of a parallel implementation of the multiplesimultaneous beam forming system 10. As can be seen from theillustration, the arrangement of the array 14 is similar to the serialimplementation of FIG. 1. However, in this implementation themultiplexers are eliminated and all n×m sensor outputs are fed directlyto the first 1D beamformer 118. The first 1D beamformer 118 paralleltransposer 120 and second one-dimensional beamformer 122 in a manneranalogous to the serial implementation, in that they preform the samematrix operations of FIG. 4. However, unlike the serial implementation,the parallel implementation replicates hardware.

FIG. 8 shows a more detailed view of the parallel implementation for a10×10 array. The one hundred samples Dx0,y0; Dx1, y0; . . . ; Dx9,y9from the sensors 12 are fed directly to a bank of ten processingelements 140-0, 140-1, 140-2, 140-3, . . . 140-9. A given processingelement 140, such as processing element 140-0, receives samples Dx0,y0;Dx1,y0; . . . , Dx9,y0 from a particular row 15-0 of the array 14; theprocessing element 140-0 thus provides the ten beamformed samplesDw0,y0; Dw1,y0; . . . ; Dw9,y0 for that row.

The ten processing elements 140 thus operate in parallel to produce 100outputs at the same time, Dw0,y0; Dw1,y0; . . . ; Dw9,y9 that representthe ten respective beams formed outputs along the x axis.

In this parallel implementation, the transposer 20 is simply the properrouting of the outputs of the first 1D beamformer 18 to the inputs ofthe second 1D beamformer 22. The second 1D beamformer 122 is implementedin much the same manner as the first 1D beamformer 118 and includes abank of ten processing elements 142-0, 142-1 . . . 142-9. The tenprocessing elements 142 operate in parallel to produce the 100beamformed outputs Dw0,v0; Dw1,v1; . . . ; Dw9,v9.

An exemplary parallel processing element 140-0 is shown in detail inFIG. 9. Similar to the serial implementation, the parallel processingelement 140-0 consists of ten tapped delay lines 144-0, 144-1, . . . ,144-9 operating in parallel that insert delays at the sensor outputs toaccount for the relative propagation delays of the signals from aparticular location. The sensor outputs are multiplied by a weightingfactor and then summed. As in the previous embodiment, different weightsare applied to different taps of a given delay line 144-0 by a set ofmultipliers 146-0-0, 146-0-1, . . . , 146-0-9. As for the serialimplementation, in order to accomplish multiple beamformingsimultaneously, multiple taps are incorporated along each delay line144. The weighted tap outputs are then summed by a set of adders 148-0,148-1, . . . , 148-9 to form a particular beam output.

In this parallel implementation the clock rate of the delay lines 144 toaccomplish real time processing may be ten times slower, for example,the clock rate need only be the same as the input sampling rate fs.However, the trade-off is that ten of the processing elements 140 arerequired to produce the necessary beamformed matrix 32.

Processing elements 142 associated with the second 1D beamformer 122 aresimilar to the exemplary processing element 140-0.

FIG. 10 shows a beamsteering implementation of the invention. Here,sensors 12 are transmitting devices, and the sample flow is in thereverse direction. Also, the multiplexers 17 are replaced bydemultiplexers 117. Otherwise, the operation of the beamsteering device10 is analogous to the operation of the beamforming device of FIG. 1.

Finally with respect to FIG. 11 the invention can be adapted to providehigher dimensional beamforming or beamsteering. For example, a threedimensional beamformer 200 may be implemented from a first 1D beamformer218, a first transposer 220, and second 1D beamfomer 222 as before,together with a second transposer 224 and third 1D beamformer 226. Thethird axis for beamforming may be an axis which is provided by a set ofsensors arranged as a three-dimensional array.

Another preferred embodiment of the invention relates to a time-domaindelay-and-sum beamforming processor that can simultaneously process thereturns of a large two dimensional transducer array. The lower-power,highly integrated beamformer is capable of real-time processing of theentire array and enables a compact, affordable unit suitable for manydifferent applications. A delay-and-sum beamformer allows a 2D array to“look” for signals propagating in a particular direction. By adjustingthe delays associated with each element of the array, the array'sdirectivity can be electronically steered toward the source ofradiation. By systematically varying the beamformer's delays and itsshading along a 2D imaging plane, a 2D scan response of the illustratedarray can be measured and resulting 2D images representing the 2Dradiation sources can be created.

A schematic diagram of a time-domain beamforming device for a 3Dultrasound/sonar imaging system 300 is illustrated in FIG. 12. Thesystem can provide continuous real-time large area 2D scanned imagesthroughout a field of view at 30 frames per second or more. The imagesize is entirely programmable which can be either 128 by 128 or 256 by256, for example. The delay-and-sum beamforming approach enables targetrange information to be obtained from the time-of-flight calculations.When a target area is identified by the electronically steerable imagingsystem, the beamforming electronics can be adjusted to zoom-in to asmaller field-of-view for high-resolution imagery. Furthermore, for agiven peak transmit intensity, a matched filter 312 can be applied tothe beamformed outputs to provide additional sensitivity.

As shown in FIG. 12, preamplifier time-gain control 302 and broadbandsampling 304 are performed on the transducer output signals.Programmable delaying 306, shading 308 and summing 310 are performed togenerate the beamformed outputs. After match filtering 312, theresulting 2D image can be displayed 314.

The use of coded or spread spectrum signaling has gained favor in thecommunications community. It is now routinely used in satellite,cellular, and wire-line digital communications systems. In contrast, theapplication of this technique to acoustic systems has been preventedprimarily due to signal propagation conditions and the relatively slowspeed of sound in water (1500 m/s) or air when compared withelectromagnetic propagation.

Despite these difficulties, the benefits of using coded signals inunderwater acoustic systems, for example, offers the potential forhigh-resolution imaging while significantly lowering the probability ofexternal detection. These signals also provide signal processing gainthat improves the overall system detection sensitivity.

Direct sequence modulation is the modulation of a carrier signal by acode sequence. In practice, this signal can be AM (pulse), FM,amplitude, phase or angle modulation. It can also be a pseudorandom orPN sequence comprised of a sequence of binary values that repeat after aspecified period of time.

The processing gain realized by using a direct sequence system is afunction of the signal transmitted compared with the bit rate of theinformation. The computed gain is the improvement resulting from the RFto information bandwidth tradeoff. Using direct-sequence modulation, theprocess gain is equal to the ratio of the RF-spread spectrum signalbandwidth divided by the information rate in the baseband channel,G_(p)=BW_(RF)/R, where R is typically expressed in bits/Hz for digitalcommunications.

The objective of a beamforming system is to focus signals received froman image point onto a transducer array. By inserting proper delays in abeamformer to wavefronts that are propagating in a particular direction,signals arriving from the direction of interest are added coherently,while those from other directions do not add coherently or cancel. For amulti-beam system, separate electronic circuitry is necessary for eachbeam.

Using conventional implementations, the resulting electronics rapidlybecome both bulky and costly as the number of beams increases.Traditionally, the cost, size, complexity and power requirements of ahigh-resolution beamformer have been avoided by “work-around” systemapproaches which form a number of transducer elements typically used inthe sonar array. A typical configuration uses a center beam togetherwith four adjacent beams aimed left, right, above and below the center.The beams are each formed from fifty or more elements in an array eachphased appropriately for the coherent summation in the five directionsof interest. The advantage of using so many elements is narrowerbeamwidths when compared with a smaller array, however, knowledge of theoutside world is still based on a five pixel image. For real-time 3Dhigh-resolution sonar imaging applications, a preferred embodimentutilizes an electronically steerable two-dimensional beamformingprocessor based on a delay-and-sum computing algorithm.

A delay-and-sum beamformer allows a 2D array to “look” for signalspropagating in particular directions. By adjusting the delays associatedwith each element of the array, the array's “look” direction or field ofview can be electronically steered toward the source of radiation. Bysystematically varying the beamformer's delays and its shading orapodization along a 2D imaging plane, a 2D scan response of the arraycan be measured and resulting images representing the 2D radiationsources can be generated. To realize such a delay-and-sum beamformer, aprogrammable delay line is needed at each receiver. However, as thearray is scanning through the imaging plane, there are two difficultimplementation issues: first, each delay line has to be long enough tocompensate for the path differences of a large area array, and second,the delay value has to be adjusted at each clock cycle for proper beamsteer(i.e., the time-of-flight from the radiation source to the focalpoint has to be calculated at every clock cycle). For example, for a 10m range requirement with a resolution of one to two centimeters dictatesan array aperture in the range of 40 cm. To realize a thirty degreescanning volume, a maximum delay of 70 ps. This implies that a2,300-stage delay line and a 12-bit control word are needed at eachreceiver to achieve the time-of-flight delay requirements. The longdelay and large number of digital I/Os would set an upper limit on howmany processors can be integrated on one chip. For example, for a64-channel time domain beamforming electronics, a straightforwardimplementation would require 64 2,300-stage delay lines and 768 digitalI/O pads. Such a large area chip and large number of I/O connectionswould make the implementation impractical.

An electronic beamforming structure is described to circumvent theimpractically long delay line requirement and a delay-update computationbased on the determination of time-of-flight surface coordinates ispresented to reduce the digital I/O requirement. This electronicprogrammable beamforming structure functions as an electronicallyadjustable/controllable virtual acoustic lens. For this reason, thisdevice is referred to herein as an electronically-controlled conformallens.

An electronically-adjustable acoustic conformal lens uses a dividedsurface of a 2D transducer array in which plane “tiles” of relativelysmall subarrays are provided. As depicted in the embodiment of FIG. 13,the tiles/subarrays 320 are made small enough so that when an object isplaced within the field-of-view of the imaging system, the incidentradiation 322 from the object toward each “tile” can be treated using afar-field approximation. Additional delay elements are incorporatedwithin each subarray to allow all subarrays to be coherently summed(i.e., global near-field beamforming can be achieved by delaying andthen summing the outputs from all subarrays). The delay-and-sumbeamformer allows each subarray 324 to “look” for signals radiating froma particular direction as illustrated by the differences betweenconfiguration 324 a and configuration 324 b. By adjusting the delaysassociated with each element of the array, the array's viewing angledirection can be electronically steered toward the source of radiation.The delay line requirement for each element in the sub-array can be asshort as several hundred stages. Only a single long delay for globalsumming is needed on each subarray processor.

A detailed diagram of an electronically-controlled beamforming system inaccordance with the invention is shown in FIG. 14A. This system consistsof a bank of parallel sub-array processors 330 ₁ to 330 _(N). Eachprocessor is a single integrated silicon circuit that comprises twocomponents: a 2D sub-array beam former 332 for far-fieldbeamsteering/focusing and an additional delay line 334 to allowhierarchical near-field beamforming of outputs from each subarray. Aspreviously mentioned, the delays associated with each receiver elementhave to be adjusted to allow the subarray to “look” for signals arrivingfrom a particular direction. As can be seen in FIG. 14A, for anm-element sub-array, m-parallel programmable tapped delay lines 340 ₁ to340 _(m) are used for delay adjustment. Within each delay line, atime-of-flight computation circuit 342 is used to select the tapposition output from a charge-domain circuit that non-destructivelysenses the tapped-delay line output. Inaccuracy of this charge sensingmechanism is only limited by the charge transfer inefficiency which isless than 10⁻⁶. As a result, the delay can be dynamically adjusted atevery clock cycle where the delay resolution is determined by the clockrate. Except for the clock skew, which can be controlled to less thanIns, there are no other spurious or dispersive effects. Each receiverhas a multiplier 344 for beam shading/apodization. Within eachprocessor, all the multipliers share a common output 346. The summedcharge is then applied to a second tapped delay line 350, which allowsthe delay from each subarray be adjusted so that all the subarrays canlook at the same source of radiation. A charge-domain A/D converter 352is used so that hierarchical summing 354 can be output digitally.

Shown in FIGS. 14B and 14C are systems for 2D sonar beamformer withdownconversion. The first embodiment shown in FIG. 14B depicts thedownconversion following the matched filter 345. A complex-valuedmultiply 347 is performed, followed by low-pass filtering 353 andsample-rate down-conversion 355. The absolute magnitude is then taken toretrieve the envelope of the signal. The A/D conversion can follow thecomplex-valued multiplication, however, this embodiment uses an A/D ineach Hierarchial Nearfield BF block.

The down converter of FIG. 14C is shown as the first operation 357 ineach channel of a submodule. Although this can be a preferred method toreduce the signal-bandwidth/data rates through the remainder of thesystem, it is a more hardware intensive system. The multiplier 361generates in phase (I) and quadrature (Q) components 363, 365 that arelow pass filtered 367, converted 369 and summed 371 prior to delay 358.

By systematically varying the beamformer's delays and its shading alonga 2D imaging plane, a rectilinear 2D scan pattern 360 of the array canbe measured and resulting 2D images representing the 2D radiationsources can be created, see FIG. 15. The system can provide continuousreal-time large area scanned images throughout a large field of view at30 frames/s or more. The delay-and-sum beamforming system providestarget range information to be obtained from the time-of-flightcalculations. When a target area is identified by the electronicallysteerable sonar system, the beamforming electronics 364 can be adjustedto zoom-in to a smaller field-of-view for high-resolution imagery.Furthermore, for a given peak transmit intensity, a matched filter canbe applied to the beamformed outputs to provide additional sensitivity.A low-power, finite-impulse-response (FIR) filter can be used toimplement the matched filter at the output of the beamforming process toimprove the system signal to noise ratio.

In real-time imaging applications, focus-and-steer images requireknowledge of the time of flight from each source to each receiver in anarray. To compute a new point on any time-of-flight surface requiresfinding the square root of the sum of squares, which is acomputationally intensive task. A delay-update computation method can beused which reduces the determination of the rectangular coordinates of anew point on any time-of-flight surface to the computation time of asingle addition. It is well-known that the method of moments can be usedto synthesize basis functions that represent an arbitrarymultidimensional function. Although the complete basis requires thedetermination of infinitely many coefficients, a finite-degree basisfunction can be generated using a least-mean-square (LMS) approximation.The specific form of the finite-degree basis depends on functionalseparability and limits of the region of support. Using theforward-difference representation of the truncated moments basis, a newfunctional value can be computed at every clock cycle. If thecomputation is performed within a square region of support, thedirection of the finite difference corresponds to the direction that thefunction is computed. For example, functional synthesis from theupper-right to lower-left corners within the region of support impliesthe computation of a multidimensional, backward differencerepresentation. Conversely the multi-dimensional, forward-differencerepresentation, presented above, allows functional synthesis to proceedfrom the lower-left to the upper-left comers within the region ofsupport. This approach produces images at least an order of magnitudefaster than conventional time-of-flight computation.

In practice, the complete moments basis representation of a surface canbe degree-limited for synthesis. One truncation method is to approximatef(x,y) with a bivariate polynomial of degree M. The bi-M^(th) degreeapproximation can be written as${\hat{f}( {x,y} )} = {\sum\limits_{p = 0}^{M}{\sum\limits_{q = 0}^{M}{{\hat{a}}_{p,q}x^{p}y^{q}}}}$

where â can be derived based on the LMS criterion,${\frac{\partial}{\partial a_{p,q}}{\int_{x_{1}}^{x_{2}}{\int_{y_{1}}^{y_{2}}{\lbrack {{f( {x,y} )} - {\hat{f}( {x,y} )}} \rbrack^{2}\quad {x}\quad {y}}}}} = 0.$

Once the coefficients â_(p,q) of the bi-Mth degree polynomial{circumflex over (f)}(x,y) possess positive-integer powers of x and y,it can be formulated as a stable, forward-difference equation. Ingeneral, (M+1)² forward-difference terms are sufficient to describe apolynomial whose highest degree in x and y is M. The terms completelyspecify {circumflex over (f)}(x,y) within its region of support.

Based on the assumption that the surface is to be scanned in a rasterfashion and has been scaled, the step size is 1. For this case, thefirst and second forward differences in one dimension are

Δ¹ _(x)={circumflex over (f)}(x₀+1, y₀)−{circumflex over (f)}(x₀,y₀),

Δ² _(x)={circumflex over (f)}(x₀+2, y₀)−2{circumflex over (f)}(x₀+1,y₀)+{circumflex over (f)}(x₀, y₀)

Using these forward differences, a second-degree polynomial in onedimensional can be written in difference form as${\hat{f}( {{x_{0} + k},y_{0}} )} = {{\hat{f}( {x_{0} + y_{0}} )} + {\lfloor \begin{matrix}{k - 1} \\k\end{matrix} \rfloor \Delta_{x}^{1}} + {\lfloor \begin{matrix}{k - 2} \\k\end{matrix} \rfloor \Delta_{x}^{2}}}$

where $\lfloor \begin{matrix}k \\n\end{matrix} \rfloor = {\frac{k!}{{n!}{( {n - k} )!}}.}$

It follows that the two-dimensional forward differences can be obtainedby evaluating the cross product term in {circumflex over (f)}(x,y),${\Delta_{x}^{n}\Delta_{y}^{1}} = {\sum\limits_{p = 0}^{n}{\sum\limits_{q = 0}{( {- 1} )^{n + 1 - p - q}\lfloor \begin{matrix}p \\n\end{matrix} \rfloor \lfloor \begin{matrix}q \\1\end{matrix} \rfloor {\hat{f}( {{x_{0} + p},{y_{0} + q}} )}}}}$

A CMOS computing structure can be used to perform functional synthesisusing the forward-difference representation of a multidimensional,finite-degree polynomial. This implementation allows the synthesis ofarbitrary functions using repeated additions with no multiplications. Anexample of this computing structure 370 is presented in FIG. 16 for atwo dimensional, first-degree, forward difference realization. As shownin FIG. 16 each register 372, represented by a rectangular box, containsthe appropriate forward-difference term. Switches, which are locatedbetween registers, determine whether the x or y direction issynthesized. The advantage of this structure is that it allows additionsto occur simultaneously at each of the adders 376. Thus only oneaddition time is required to produce the next function value. For amulti-channel processor, each channel contains its own functional updatecircuitry. As the beam is steered through a given imaging plane, thedelay requirements for each channel are computed in parallel and can beupdated within one clock period. For a 64 channel beamformingprocessors, at a 40 MHz clock rate, a continuous delay update rate of 30billion bits/s can be achieved based on this approach.

Using this approach, instead of the alternative 11 bits/channel, thedigital connectivity can be reduced to 1 bit/channel followed by on-chipcomputation circuitry to generate the equivalent 12 bit value whilemaintaining the 30 billion bits/s parallel update rate.

Preferred elements of a high performance ultrasound imaging systemincludes the ability to provide features such as 1) multi-zone transmitfocus, 2) ability to provide different pulse shapes and frequencies, 3)support for a variety of scanning modes (e.g. linear, trapezoidal,curved-linear or sector), 4) multiple display modes such as M-mode,B-mode, Doppler sonogram and color-flow mapping (CFM). Preferredembodiment for such a system are based on the integrated beamformingchip described herein. All five systems can provide the desiredcapabilities described above, with different emphasis on physical sizeand power consumption.

In the system 400 shown in FIG. 17A, integrated circuits (modules) forbeamforming 414, transmit/receive selection 416 and a preamplifier/TGCchip 418 are fully integrated within the probe-housing 402 with thetransducer array 420, as is the system controller 422. The systemcontroller 422 maintains proper clocking and operation of the memory 424to assure continuous data output and also generates clock and controlsignals to indicate the intended recipient (among the three modules) ofdata packets at the memory output port. The controller 422 alsointerfaces with the host computer 406 (a generic personal computer, PC)via PCI bus or FireWire 426 along interface 404 to allow the host toupdate on-probe memory or to receive ultrasound data from the probe.(All signals pass between the host PC and probe via PCI or Firewire.)The tasks of signal down conversion, scan conversion (reformatting fordisplay in a Cartesian coordinate system) and post signal processing areperformed by microprocessing system 412 of the host PC. Additionally, inour system design, color-flow map and Doppler sonogram computations canbe performed by two different implementations: a hardware-basedimplementation and a software implementation as shown in FIG. 17A. It isimportant to note that a dedicated Doppler-Processor chip can be mountedon a back-end (within the PC) card 408 and be used as a co-processor tothe host computer to accomplish the Doppler sonogram computation and CFMcomputation. However, FIG. 17A depicts an implementation where the CFMand sonogram computations are performed by the host PC in software andoutput to display 410.

FIG. 17B depicts a system 440 that allows a more compact probe housing442 or scanhead. In this design, the transducer array 444 is mounted ina probe housing 442 connected to a dedicated processing module 446 viacoaxial cable 448. The component modules (beamforming, preamp/TGC andtransmit/receive chips) are housed in the overall processing module 446,which communicates with the host PC 452 via PCI or Firewire 450.Multiple-beamforming is provided by this system 446. Control andsynchronization is performed by the system controller located in theprocessing module.

Charge-domain processors 470 (CDP) for beamforming can also be fullyintegrated into a dedicated system, as shown in FIG. 17C. In this, thetransducer array is housed in a separate scanhead unit 466 and theconnected to the host using coaxial cables 464. The suite of MCDPprocessing modules 470 (transmit/receive, preamp/TGC and beamformingchips are physically housed within the main system unit 462. This designsupports multiple-beam beamforming with use of parallel CDP beamformingchips. This system covers the case in which beamforming tasks for anexisting ultrasound systems can be performed by CDP devices by replacingthe original beamforming modules with their CDP equivalents.

A preferred embodiment for a compact scanhead that minimizes noise andcable loss is shown in FIG. 17D. This system 480 integrates thetransmit/receive chip and preamp/TCG chip on the probe 482 with thetransducer array. The system controller, memory and beamforming chip (orchips for multiple beamforming) are housed in a separate processingmodule 486 connected via PCI or Firewire to the host PC 488 whichperforms down conversion, scan conversion and post signal processing.This design reduces the size of the scanhead probe, as compared to thedesign in FIG. 17A.

The semi-integrated front-end probe 482 described in FIG. 17D, where thetransmit/receive chip and preamp/TGC chip are placed on the probe withthe transducer array, is coupled with a cable 484 to module 486 thatuses CDP beamformers. This design compares to that in FIG. 17C, whichdescribes use of CDP beamforming in an ultrasound system. The differenceis that here additional processing is performed on the scanhead,reducing noise and cable losses relative to the system of FIG. 17C whereall processing is performed after data are transmitted via coaxial cablefrom the scanhead to the host. System 490 of FIG. 17E retains the sameor similar probe design as FIG. 17D, however the elements of theprocessing module 486 of FIG. 17D have been included in the processingsystem 492 of FIG. 17E.

The multi-dimensional beamformer processing system is a time-domainprocessor that simultaneously processes the transmit pulses and/orreturns of a two-dimensional array 502. For transmit beamforming, thesystem can be used either in a bi-static mode, utilizing a separatetransmit transducer array 502, or it can use the receive array 504 fortransmit focus as well. As shown in FIG. 18A, for the bi-staticconfiguration 500, the separate transmitter 502 can be a single-pingimplementation that illuminates the whole image plane 506 with a singletransmission. Alternatively, transmission can be implemented in asparsely packed beam pattern that covers the image plane 514 as shown inFIG. 18B. For transmit beamforming, a transmit control chip is neededfor providing delays to the high-voltage driving pulses applied to eachtransducer element of array 512 such that the transmitted pulses arewill be coherently summed on the image plane at the required transmitfocus point 516.

The multi-channel transmit/receive chip performs the functions oftransmit beamforming, switching between transmit receive modes(TRswitch), and high-voltage level shifting. As shown in FIG. 19, themulti-channel transmit/receive chip consists of, a global counter 542which broadcasts a master clock and bit values to each channelprocessor. A global memory 544 which controls transmit frequency, pulsenumber, pulse sequence and transmit/receive select. A local comparator546 which provides delay selection for each channel. For example, with a60-MHz clock and a 10-bit global counter, the comparator can provideeach channel with up to 17-ms delay. A local frequency counter 548 whichprovides programmable transmit frequency. A 4-bit counter provides up tosixteen different frequency selections. For example, using a 60-MHzmaster clock, a 4-bit counter can be programmed to provide 60/2=30 MHz,60/3=20 MHz, 60/4=15 MHz, 60/5=12 MHz, 60/6=10 MHz and so on. A localpulse counter 550 which provides different pulse sequences. For example,a 6-bit counter can provide programmable transmitted pulse lengths fromone pulse up to 64 pulses. A locally programmable phase selector 552which provides sub-clock delay resolution. For example, for a 60-MHzmaster clock and a two-to-one phase selector provides 8-ns delayresolution.

While typically the period of the transmit-chip clock determines thedelay resolution, a technique called programmable subclock delayresolution allows the delay resolution to be more precise than the clockperiod. With programmable subclock delay resolution, the output of thefrequency counter is gated with a phase of the clock that isprogrammable on a per-channel basis. In the simplest form, a two-phaseclock is used and the out put of the frequency counter is either gatedwith the asserted or deasserted clock. Alternatively, multiple skewedclocks can be used. One per channel can be selected and used to gate thecoarse timing signal from the frequency counter. In anotherimplementation 560 shown in FIG. 20, the T/R switch and the high-voltagelevel shifter 562 are separated from the other components to allowhigh-voltage operation.

By systematically varying beamformer delays and shading along a 2Dimaging plane, a 2D scan response of a 2D transducer array can bemeasured and resulting 2D images representing the 2D radiation sourcescan be created. This method can be extended to scan not just a 2D planebut a 3D volume by systematically changing the image plane depth as timeprogresses, producing a seqeuence of 2D images, each generated by the 2Dbeamforming processors as described above. The sequence of imagesdepicts a series of cross-section views of a 3D volume as shown in FIG.21A. In this manner a complete scan of a 3D object can be obtained.There are two modes of operation: sequential or parallel. In sequentialmode, a single sterrable beamforming processor is used with the 2Darray. As shown in FIG. 21B, the image plane is serially scanned pixelby pixel (i.e. the beamforming is computed pixel-by-pixel) until thewhole image plane is processed. In parallel mode, more than onebeamforming processor is used. FIG. 21C depicts the case of twosteerable beamforming processor. At any given time, two receive beamsare formed, one by each processor. The corresponding scan pattern isshown in FIG. 21D where the image plane is divided into two halves andeach beamforming processor is used to scan half of the image plane.Consequently, the frame rate can be doubled in this parallel beamformingmode. A scan pattern generated by four parallel receive beamformingprocessors is depicted in FIGS. 22A-22C. It can be deduced that theframe rate for the four parallel-beam beamforming system can be fourtimes faster than that of a single-beam beamforming system. In general,for an m-parallel receive beam system, the frame rate can be increasedby a factor m.

The same sequential vs parallel receive beamforming architecture isapplicable to a 1D linear or curved linear array. FIG. 23 shows, as anexample, a 192-element one dimensional array 600. In sequential mode,with a single 64-element beamforming processor used, the scan lines (thereceived beams) are formed one by one. That is to say, line 1 at 602 isformed first by processing returned echos from elements 1 through 64 ata view angel −0 (angles defined with respect to the normal directionfrom the transducer face). Line 2 is formed next by processing returnsfrom elements 64 through 128 at a normal view angle. Line 3 is thenformed by returns from elements 1 through 64 at a view angle −0+0/S, andso forth. It follows then that the (S−1)th line is formed by returnsfrom element 1 through 64 at an view angle −0/S. The Sth line is formedby returns from elements 128 through 192 at the normal direction fromthe transducer face. Finally the Lth scan line is formed at 604 byprocessing the returns from elements 128 through 192 at an view angle+0. In parallel mode, multiple beamforming processors are used inparallel. For the case of two 64-element beamforming processors, at anygiven time, two scan lines (or two beams) are formed by the firstprocessor and the odd numbered lines by the second processor. The numberof scan lines is selected based on the imaging quality requirement of agiven application. For example, an imaging system can be designed toprovide 256 scan lines, e.g. L=256 and W=64. On the other hand, for ahigh-resolution imaging application, a system can be designed to provide1024 scan line, e.g., L=1024, and S=128. It is important to note thatthe frame rate of the two-processor system can be twice as fast as thatof a single-processor system. In general, for an m-processor beamforming system, the frame rate can be increased by a factor of mrelative to a single-processor system.

A Doppler sonogram 620 can be generated using single-range-gate Dopplerprocessing, as shown in FIG. 24. The operation of this method is asfollows. A sequence of N ultrasonic pulses is transmitted at a pulserepetition frequency f_(prf) along a given view angle. The return echoes622 are range gated and only returns from a single range bin are used,meaning that only the returned signals corresponding to a region aselected distance (e.g. from depth d to d+Sd) from the transducer arrayalong the selected viewing angle are processed to extract Dopplerinformation. The velocity profiles of scatterers in the selected regioncan be obtained by computing the Doppler shifts of the echoes receivedfrom the scatterers. That is, Fourier transformation at 624 of thereceived time-domain signal provides frequency information, includingthe desired Doppler shifts, f_(d). The velocity distribution of thescatterers in the region of interest can be obtained from therelationship${{fd} = {\lbrack \frac{2v}{c} \rbrack f_{c}}},$

where c is the speed of sound in the transmitting medium and f_(c) isthe center frequency of the transducer. As an example, if N=16 andf_(prf)=1 KH_(z), the above equation can be used to generate a sonogramdisplaying 16 ms of Doppler data. If the procedure is repeated everyN/f_(prf) seconds, a continuous Doppler sonogram plot can be produced.

The following relates to a pulse-Doppler processor for 3D color flow mapapplications. The pulsed systems described here can be used forinterrogating flow patterns and velocities, such as the flow of bloodwithin a vessel. The time evolution of the velocity distribution ispresented as a sonogram, and different parts of the vessel can be probedby moving the range gate and varying its size. The ultimate goal forprobing the circulatory system with ultrasound is to display a full mapof the blood flow in real time. This enables the display of velocityprofiles in vessels and the pulsatility of the flow. One step towardmeeting this goal is to use color flow mapping (CFM) systems. They arean extension of the multigated system described in the above paragraph,as the blood velocity is estimated for a number of directions (scanlines) in order to form an image of flow pattern. The velocity image issuperimposed on a B-mode image, and the velocity is coded as colorintensity and direction of flow is coded as color. For example, a redcolor indicates flow toward and blue flow away from the transducer. Acolor-flow map based on pulsed Doppler processing is shown here in FIG.25. Instead of a single range bin, data from J range bins, whichcorrespond to returns from different depths, are processed in parallel.At a given scan angle, after N-pulse returns at array 640 are processed,the outputs represent JXN range-vs-Doppler distribution. For a givenrange bin, e.g., a given depth, the data can be used to generate a Nvelocity distribution profile. Mean velocity calculated from thisdistribution profile can be used to produce one point on the color-flowmap of a given depth, the standard deviation can be used to assessturbulence. If the procedure is repeated every scan angle such that thewhole image plane has been covered, a 3D color-flow map which depicts asa sequence of 2D color-flow plots, each one corresponding to differentdepths at d₁, d₂ and d₃ can be produced.

Algorithms can be used to compute the first moment and the velocitydistribution of the pulse returns. In stead of a Fourier transform-basedcomputation, a cross correlation technique, described in Jensen, JorgenA., “Estimation of Blood Velocities Using Ultrasound”, Cambridge Univ.Press 1996, the entire contents of which is incorporated herein byreference, can also be used to produce a similar color flow map.Furthermore, an optimal mean velocity estimation can be used.

Mean velocity (i.e., first spectral moment) estimation is central tomany pulse Doppler data processing. With applications such as Color FlowMap for displaying mean velocity, inherent requirements for high-scanrate and fine (azimuth) scan patterns restrict the allocation of pulsesamples to but a small number per range cell. As a result, theseapplications operate at times near the fundamental limits of theirestimation capabilities. For such specific needs, an optimal DopplerCentroid estimation in the case of known spectral width (SW) andsignal-to-noise ratio (SNR) is described.

Let us consider the usual probabilistic model for pulse-Dopplerobservation of a complex-valued vector return, z₁, z₂ . . . , z_(N)corresponding to a single range cell with N equally-spaced samples of acomplex Gausian process with covariance matrix T=E[ZZ*]. We also adoptthe common single-source sample-covariance model consisting ofGaussian-shaped signal plus uncorrelated additive noise:

r_(n)=Se^(−8(πσ) ^(_(v)) ^(nπ)) ²e^(−j4π{overscore (v)}nτ/λ)+V_(noise)δ_(n)(0≦n<N)

where the model parameters {overscore (v)} and σ_(n) represent meanDoppler velocity and Doppler SW, λ is the transducer RF wavelength, andS and N respectively represent signal to noise power magnitudes. Let usdefine $G = {{G(\sigma)} = \begin{bmatrix}{p(0)} & {p(1)} & . & {p( {N - 1} )} \\{p(1)} & {p(2)} & . & {p( {N - 2} )} \\. & . & . & . \\. & . & . & . \\{p( {N - 1} )} & {p( {N - 2} )} & . & {p(0)}\end{bmatrix}}$${{\text{where}\quad {p(n)}} = e^{{- {({\pi n\sigma})}^{2}}/2}},{\sigma = \frac{\sigma_{v}}{V_{\lambda}}},{{{and}\quad V_{\lambda}} = {\frac{\lambda}{4\pi}.}}$

In the case of maximum likehood (ML) estimation, it results in a simplemean velocity expression$\omega_{ML} = {\arg \quad \min \quad {{\mathbb{R}e}( {\sum\limits_{n = 0}^{N - 1}{r_{n}^{\Gamma}e^{- {j\omega n}}}} )}}$

where r_(n) ^(Γ) is the weighted autocorrelation estimate defined by${r_{m}^{\Gamma} \equiv {{\sum\limits_{i = 0}^{N - n - 1}{Z_{i}^{*}\gamma_{i,j}}} + {nZ}_{i + n}}},$

where$\omega = {\frac{\overset{\_}{v\quad}\pi}{V_{\lambda}}\quad {and}\quad \gamma_{i,k}}$

and the element of the matrix Γ,

where Γ=Γ(σ,η)=[S G+V_(noise)I]⁻¹

and I=diag[11 . . . 1].

The generic waveform for pulse-Doppler ultrasound imaging is shown inFIG. 26. The waveform consists of a burst of N pulses 660 with as manyrange depth samples as needed are collected for each pulse in the burst.FIG. 26 also shows a block diagram of a signal processor for thisimaging technique, where the returned echoes received by each transducerare sampled and coherently summed prior to in-phase and quadraturedemodulation. The demodulated returns are converted to a digitalrepresentation, and then stored in a buffer memory until all the pulsereturns comprising a coherent interval are received. The N pulse returnscollected for each depth are then read from memory, a weightingsequence, υ(n), is applied to control Doppler sidelobes, and an N-pointFFT 661 is computed. During the time the depth samples from one coherentinterval are being processed through the Doppler filter, returns fromthe next coherent interval are arriving and are stored in a second inputbuffer. The FFT output can be passed on directly to a display unit orfurther processed by time-averaging Doppler prior to display.

The CDP device described here performs all of the functions indicated inthe dotted box 662 of FIG. 26, except for A/D conversion, which is notnecessary because the CDP provides the analog sampled data function.This CDP Pulsed-Doppler Processor (PDP) device has the capability tocompute a matrix-matrix product, and therefore has a much broader rangeof capabilities. The device computes the product of two real-valuedmatrices by summing the outer products formed by pairing columns of thefirst matrix with corresponding rows of the second matrix.

In order to describe the application of the PDP to the Doppler filteringproblem, we first cast the Doppler filtering equation into a sum ofreal-valued matrix operations. The Doppler filtering is accomplished bycomputing a Discrete Fourier Transform (DFT) of the weighted pulsereturns for each depth of interest. If we denote the depth-Dopplersamples g(kj), where${g( {k,j} )} = {\sum\limits_{n = 0}^{N - 1}{{v(n)}{f( {n,j} )}{\exp ( {{- {j2}}\quad \pi \quad {{kn}/N}} )}}}$

The weighting function can be combined with the DFT kernel to obtain amatrix of Doppler filter transform coefficients with elements given by

w(k,n)=w_(k,n)=ν(n)exp(−j2πkn/N)

The real and imaginary components of the Doppler filtered signal can nowbe written as$g_{r,{kj}} = {\sum\limits_{n = 0}^{N - 1}( {{w_{r,{kn}}f_{r,{nj}}} - {w_{i,{kn}}f_{i,{nj}}}} )}$$g_{r,{kj}} = {\sum\limits_{n = 0}^{N - 1}( {{w_{r,{kn}}f_{i,{nj}}} - {w_{i,{kn}}f_{i,{nj}}}} )}$

In Eq.(4), the double-indexed variables may all be viewed as matrixindices. Therefore, in matrix representation, the Doppler filtering canbe expressed as matrix product operation. It can be seen that the PDPdevice can be used to perform each of the four matrix multiplicationsthereby implementing the Doppler filtering operation.

A block diagram of the PDP device is shown in FIG. 26. The deviceincludes a J-stage CCD tapped delay line 664, J CCD MDACs 666(multiplying digital-to-analog converters), JXK accumulators, JXKDoppler sample buffers 668, and a parallel-in-serial out (PISO) outputshift register 670. The MDACs share a common 8-bit digital input onwhich elements from the coefficient matrix are supplied. The tappeddelay line performs the function of a sample-and-hold, converting thecontinuous-time analog input signal to a sampled analog signal.

A two-PDP implementation for color flow mapping in a ultrasound imagingsystem is shown in FIG. 27. In this device, during one pulse repetitioninterval, the top PDP component computes all the terms of the formw_(r)f_(r) and w_(s)f_(r) as shown in Eq. 5, while the bottom componentcomputes terms of the form −w_(i)f_(i) and w_(r)f_(i). The outputs ofeach component are then summed to alternately obtain g_(r) and g_(i).Doppler and color flow map processing involves significant computation.This processing can be accomplished in software using a general-purposemicroprocessor. The presence of instructions optimized for matrix-matrixoperations, such as Intel MMX feature set, can substantially improveperformance. A software flow chart for color-flow map computation 700based on the Fourier transform computation is shown in FIG. 28. Afterinitialization 702, the downconverted data is obtained 704 and thepointer P is at the beginning of the scan angle 706, the range datacollected and stored 708, a weighting function is applied 710, theFourier transform is computed 712, the magnitude z(k) is computed foreach frequency followed by the computation of first and second moments716 and displayed 718 in color. The pointer is incremented and each scanline is processed as needed.

A software flow chart 740 for color-flow map computation based on theoptimal mean velocity estimation described above is shown in FIG. 29.After initialization 742 the downconverted data is obtained 744 and thepointer P is at the beginning of the scan angle 746, the range data iscollected and stored 748, a weighting autocorrelation function 750 iscomputed based on the Equation (3). It follows then a mean velocity canbe estimated 752 based on Equation (2). The mean velocity is displayed754 in color. The pointer is incremented and each scan line is processedas needed.

A software flow chart for color-flow map computation based on thecross-correlation computation 760 is shown in FIG. 30. Afterinitialization 762 the range data is obtained 766. The cross correlationis computed 768 and averaged 770. The velocity distribution 772, firstand second moments 774 are computed and displayed 776. The range date isincreased until all data on a given scan line are all processed. Theprocess repeats for the next scan line until all the scan lines along acompleted image plane are processed.

While we have shown and described several embodiments in accordance withthe present invention, it is to be understood that the invention is notlimited thereto, but is susceptible to numerous changes andmodifications as known to a person skilled in the art, and we thereforedo not wish to be limited to the details shown and described herein butintend to cover all such changes and modifications as are obvious to oneof ordinary skill in the art.

While this invention has been particularly shown and described withreferences to preferred embodiments thereof, it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the spirit and scope of theinvention as defined by the appended claims.

What is claimed is:
 1. A beamforming device, comprising: a sensor arraythat provides array signals; a first programmable beamforming tappeddelay line device, coupled to the sensor array, that generates delayedoutput signals based on the array signals; and a second programmablebeamforming tapped delay line device, coupled to the first tapped delayline device, the second tapped delay line device generating arepresentation of a region of interest based on the delayed outputsignals.
 2. The beamforming device of claim 1 further comprising: atranspose device, coupled between the first and second tapped delay linedevices, for transposing the delayed output signals generated by thefirst tapped delay line device such that the second tapped delay linedevice generates the representation of the region of interest based onthe transposed delayed output signals.
 3. The multidimensionalbeamforming device of claim 2 wherein the first tapped delay line deviceforms at least a portion of a first one-dimensional beamformer, andwherein the second tapped delay line device forms at least a portion ofa second one-dimensional beamformer.
 4. The multidimensional beamformingdevice of claim 3 wherein the first one-dimensional beamformer formsbeams along a first set of angles formed with respect to a first plane,and wherein the second one-dimensional beamformer forms beams along asecond set of angles formed with respect to a second plane that isnon-planar with the first plane.
 5. The beamforming device of claim 1wherein the sensor array includes subarrays of sensor elements.
 6. Thebeamforming device of claim 5 wherein the first programmable tappeddelay line device includes groups of first integrated circuit delaylines corresponding to the subarrays of the sensor array, each firstdelay line of a group being coupled to a sensor element of that group'scorresponding subarray.
 7. The beamforming device of claim 6 wherein thesecond programmable tapped delay line device includes second delaylines, each second delay line being coupled to one of the groups offirst delay lines.
 8. The beamforming device of claim 1 wherein thefirst programmable tapped delay line device operates such that at leasta portion of the delayed output signals form a first representationhaving a first resolution, the representation generated by the secondtapped delay line device having a second resolution that is lower thanthe first resolution.
 9. The beamforming device of claim 1 wherein thefirst programmable tapped delay line device is arranged to perform afar-field approximation, and wherein the second programmable tappeddelay line device is arranged to perform a near-field approximation. 10.A method for beamforming comprising steps of: obtaining array signalsfrom a sensor array; programming a first programmable tapped integratedcircuit delay line device to generate delayed output signals based onthe array signals; and programming a second programmable tapped delayline device to generate a representation of a region of interest basedon the delayed output signals.
 11. The method of claim 10 furthercomprising a step of transposing the delayed output signals generated bythe first programmable tapped delay line device such that the secondprogrammable tapped delay line device generates the representation ofthe region of interest based on the transposed delayed output signals.12. The method of claim 11 wherein the step of programming the firstprogrammable tapped delay line device includes forming beams along afirst set of angles formed with respect to a first plane, and whereinthe step of programming the second programmable tapped delay line deviceincludes forming beams along a second set of angles formed with respectto a second plane that is non-planar with the first plane.
 13. Themethod of claim 10 wherein the step of programming the firstprogrammable tapped delay line device includes forming a firstrepresentation having a first resolution, forming a secondrepresentation generated by the second programmable tapped delay linehaving a second resolution that is lower than the first resolution. 14.The method of claim 10 wherein the step of programming the firstprogrammable tapped delay line device includes performing a far-fieldapproximation, and wherein the step of programming the secondprogrammable tapped delay line device includes performing a near-fieldapproximation.
 15. A multidimensional beamforming device comprising: amultidimensional sensor array; and a time domain processing device thatgenerates transmit signals for a transmission array and that receivessignals from the sensor array, the processing device forming delayedoutput signals with a programmable delay line device to generate arepresentation of a region of interest.
 16. The device of claim 15wherein the sensor array comprises a plurality of independentlycontrollable subarrays.
 17. The device of claim 15 wherein the devicecomprises a delay line device including a charge coupled device.
 18. Thedevice of claim 15 further comprising a down conversion circuit.
 19. Thedevice of claim 15 further comprising a scan controller to scan thearray across an image plane.
 20. The device of claim 16 furthercomprising a plurality of delay lines for each subarray, an output ofeach delay line being summed to provide an input into a secondprogrammable delay line.